Re-extraction from urbanized areas based on high-resolution night light images

Abstract

The definition of urbanized areas, both regionally and globally, is an important basis for urban development monitoring and management, as well as an important condition for studying social policies, economics, culture and the environment. Thanks to the development of science and technology, urban expansion is developing rapidly. The method of extracting urbanized areas quickly and accurately has become the focus of research. In the 1970s, with the beginning of the Defense Meteorological Satellite Program (DMSP), the images of night lights that provide a new method for the extraction of urbanized areas were born. However, due to the limits of spatial resolution and spectral range, it’s true that there are defects in urbanized area extraction based on OMSP-OLS nightlight images. In recent years, with the development of remote sensing technology, remote sensing data with a higher resolution emerged, providing an effective and applicable data source for urban planning monitoring.

I suppose that the images of night lights with a higher resolution have greater precision than the old ones in the extraction of urbanized areas. This work has dedicated the images of night lights (NPP-VIIRS and Luojia1-01) and the images of urbanized areas (FROM-GLC 2017) to construct a logistic regression model to evaluate and compare the accuracy of the two images of night lights in the extraction of urbanized areas. And I hope to explore the advantages of the night light images of the new generation satellite Luojia1-01 in the smaller scale studies. First, I will learn the knowledge of night light imaging to summarize and determine the necessary methods, including methods of data processing, urbanized area extraction, evaluation and etc. Second, I will process the images and data in Arcgis to obtain the values of each pixel as variables, and I will make a logistic regression model of the original and logarithmic data in SPSS. In addition, I will calculate the cross table of the 4 results with the urbanization value to obtain the probability and Kappa. Finally, I will compare and analyze the probability and Kappa, and pass the thresholds obtained to Arcgis to perform the re-extraction of urbanized areas.